Publications

@article{Medina2017,

title = {Indexing techniques to improve the performance of necessity-based fuzzy queries using classical indexing of RDBMS},

author = {J. M. Medina and C. D. Barranco and O. Pons},

url = {http://www.sciencedirect.com/science/article/pii/S0165011417303482},

doi = {10.1016/j.fss.2017.09.008},

issn = {0165-0114},

year  = {2018},

date = {2018-11-01},

journal = {Fuzzy Sets and Systems},

volume = {351},

pages = {90-107},

abstract = {It is widely known that the most effective way to implement a fuzzy database is to use a classical Relational Database Management System (RDBMS) as the basis. All these systems provide several kinds of indexing methods to improve the execution time of classical queries, but they are useless when directly applied to fuzzy queries. For this reason, in this work we propose and evaluate several fuzzy indexing techniques implemented over the indexing techniques available on classical RDBMS in order to enhance flexible queries when based on the necessity measure. As the results show, the best evaluated fuzzy indexing techniques can be implemented on top of classical RDBMS.},

keywords = {Fuzzy databases},

pubstate = {published},

tppubtype = {article}

}

@article{Medina2016,

title = {Evaluation of Indexing Strategies for Possibilistic Queries Based on Indexing Techniques Available in Traditional RDBMS},

author = {J. M. Medina and C. D. Barranco and O. Pons},

url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/int.21820

https://onlinelibrary.wiley.com/doi/pdf/10.1002/int.21820},

doi = {10.1002/int.21820},

year  = {2016},

date = {2016-10-18},

journal = {International Journal of Intelligent Systems},

volume = {31},

number = {12},

pages = {1135-1165},

abstract = {A common way to implement a fuzzy database is on top of a classical relational database management systems (RDBMS). Given that almost all RDBMS provide indexing mechanisms to enhance classical query processing performance, finding ways to use these mechanisms to enhance the performance of flexible query processing is of enormous interest. This work proposes and evaluates a set of indexing strategies, implemented exclusively on top of classical RDBMS indexing structures, designed to improve flexible query processing performance, focusing in the case of possibilities queries. Results show the best indexing strategies for different data a query scenarios, offering effective ways to implement fuzzy data indexes on top of a classical RDBMS.},

keywords = {Fuzzy databases},

pubstate = {published},

tppubtype = {article}

}

@article{Medina2014,

title = {A Fuzzy Temporal Object-Relational Database: Model and Implementation},

author = {J. M. Medina and J. E. Pons and C. D. Barranco and O. Pons},

url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/int.21666

https://onlinelibrary.wiley.com/doi/pdf/10.1002/int.21666},

doi = {10.1002/int.21666},

year  = {2014},

date = {2014-06-24},

journal = {International Journal of Intelligent Systems},

volume = {29},

number = {9},

pages = {836-863},

abstract = {Abstract In real world, some data have a specific temporal validity that must be appropiately managed. To deal with this kind of data, several proposals of temporal databases have been introduced. Moreover, time can also be affected by imprecision, vagueness, and/or uncertainty, since human beings manage time using temporal indications and temporal notions, which may also be imprecise. For this reason, information systems require appropriate support to accomplish this task. In this work, we present a novel possibilistic valid time model for fuzzy databases including the data structures, the integrity constraints, and the DML. Together with this model, we also present its implementation by means of a fuzzy valid time support module on top of a fuzzy object-relational database system. The integration of these modules allows to perform queries that combines fuzzy valid time constraints together with fuzzy predicates. Besides, the model and implementation proposed support the crisp valid time model as a particular case of the fuzzy valid time support provided.},

keywords = {Fuzzy databases},

pubstate = {published},

tppubtype = {article}

}

@article{Barranco2013,

title = {Building a Fuzzy Valid Time Support Module on a Fuzzy Object-Relational Database},

author = {C. D. Barranco and J. M. Medina and J. E. Pons and O. Pons},

doi = {10.1007/978-3-642-40769-7_39},

isbn = {978-3-642-40769-7},

year  = {2013},

date = {2013-05-01},

journal = {Flexible Query Answering Systems},

pages = {447-458},

abstract = {In this work we present the implementation of a Fuzzy Valid Time Support Module on top of a Fuzzy Object-Relational Database System, based on a model to deal with imprecision in valid-time databases. The integration of these modules allows to perform queries that combines fuzzy valid time constraints with fuzzy predicates. Both modules can be deployed in Oracle Relational Database Management System 10.2 and higher. The module implements the mechanisms that overload the SQL sentences: Insert, Update, Delete and Select to allow fuzzy temporal handling. The implementation described supports the crisp valid time model as a particular case of its fuzzy valid time support provided.},

keywords = {Fuzzy databases},

pubstate = {published},

tppubtype = {article}

}

@article{Medina2012,

title = {On Modeling the Behavior of Comparators for Complex Fuzzy Objects in a Fuzzy Object-Relational Database Management System},

author = {J. M. Medina and C. D. Barranco and J. R. Campaña and S. J. Castillo},

doi = {10.1080/18756891.2012.718159},

issn = {1875-6883},

year  = {2012},

date = {2012-08-01},

journal = {International Journal of Computational Intelligence Systems},

volume = {5},

number = {4},

pages = {762-774},

abstract = {This paper proposes a parameterized definition for fuzzy comparators on complex fuzzy datatypes like fuzzy collections with conjunctive semantics and fuzzy objects. This definition and its implementation on a Fuzzy Object-Relational Database Management System (FORDBMS) provides the designer with a powerful tool to adapt the behavior of these operators to the semantics of the considered application.},

keywords = {Fuzzy databases},

pubstate = {published},

tppubtype = {article}

}

@article{Medina2012b,

title = {On the Use of a Fuzzy Object-Relational Database for Flexible Retrieval of Medical Images},

author = {J. M. Medina and S. J. Castillo and C. D. Barranco and J. R. Campaña},

doi = {10.1109/TFUZZ.2012.2201726},

issn = {1941-0034},

year  = {2012},

date = {2012-08-01},

journal = {IEEE Transactions on Fuzzy Systems},

volume = {20},

number = {4},

pages = {786-803},

abstract = {This paper introduces a novel approach to medical image retrieval using a fuzzy object-relational database management system (FORDBMS). The system stores medical images along with information about the content of the image, such as the presence or absence of certain indicators of pathologies. It allows us to flexibly retrieve them on the basis of these indicators, making it possible to obtain images from patients with similar diagnosis and thus, following a common visual pattern. To illustrate the capabilities of the FORDBMS, this paper focuses on X-ray images of patients suffering from scoliosis (a medical condition in which the patient's spine is curved) from which spine descriptions are obtained. Then queries are performed to obtain a set of images with a certain curvature pattern. Results show high accuracy when evaluated by medical experts. Compared with other ad hoc content-based image retrieval systems, the one presented here is easily adaptable to other application domains, customizable, and very scalable.},

keywords = {Fuzzy databases},

pubstate = {published},

tppubtype = {article}

}

@article{Barranco2012,

title = {An impact ordering approach for indexing fuzzy sets},

author = {C. D. Barranco and S. Helmer},

url = {http://www.sciencedirect.com/science/article/pii/S0165011411000558},

doi = {10.1016/j.fss.2011.01.014},

issn = {0165-0114},

year  = {2012},

date = {2012-06-01},

journal = {Fuzzy Sets and Systems},

volume = {196},

pages = {33-46},

abstract = {We propose an approach for indexing fuzzy data based on inverted files that speeds up retrieval considerably by stopping the traversal of postings lists early. This is possible because the entries in the postings lists are organized in a way that guarantees that there are no matching items beyond a certain point in a list. Consequently, we can reduce the number of false positives significantly, leading to an increase in retrieval performance. We have implemented our approach and evaluated it experimentally, including a test on skewed and real-world data, comparing it to an approach that has previously been shown to be superior to other methods.},

keywords = {Fuzzy databases},

pubstate = {published},

tppubtype = {article}

}

@article{Chamorro-Martínez2007,

title = {Retrieving images in fuzzy object-relational databases using dominant color descriptors},

author = {J. Chamorro-Martínez and J. M. Medina and C. D. Barranco and E. Galán-Perales and J. M. Soto-Hidalgo},

url = {http://www.sciencedirect.com/science/article/pii/S0165011406004209},

doi = {10.1016/j.fss.2006.10.013},

issn = {0165-0114},

year  = {2007},

date = {2007-11-01},

journal = {Fuzzy Sets and Systems},

volume = {158},

number = {3},

pages = {312-324},

abstract = {In this paper a fuzzy approach for image retrieval on the basis of color features is presented. The proposal deals with vagueness in the color description and introduces the use of fuzzy database models to store and retrieve imprecise data. To face the color description, the concept of dominant fuzzy color is proposed, using linguistic labels for representing the color information in terms of hue, saturation and intensity. To deal with fuzzy data in our database model, we use a general approach which can support the manipulation of fuzzy objects in an object-relational database system. This allows the retrieval of images by performing flexible queries on the database.},

keywords = {Fuzzy databases},

pubstate = {published},

tppubtype = {article}

}